Tax impact on multi-stage mean-variance portfolio allocation

We investigate the sensitivity to tax change of multi‐stage portfolio allocation over a discrete time investment horizon. Special taxation rules within wrappers grouped a number of risky assets are integrated with multi‐stage linear or quadratic stochastic programming in the mean‐variance framework. The uncertainty on the returns of assets is specified as a scenario tree generated by a simulation‐based approach. We adjust different values on capital gains tax under different asset bounds and risk levels. The tax impact in the yearly reallocation of the investments for a typical case with an annual fixed withdrawal that utilizes completely the option of taper relief is also explored. Our computational results show that taxes, combined with other effects such as risk and investment upper bounds, have a significant performance impact on portfolio allocation as well as diversification over wrappers. Yet, investment strategies can be made robust to changes in taxation.     

Critical scenarios derivation methodology for mechatronic systems

This paper deals with safety in design of mechatronic systems. We propose a method based on a qualitative analysis of a Petri net model of the system. It allows deriving feared scenarios by determining the sequences of actions and state changes leading to the feared state in which the passenger's safety is no longer guaranteed. The Petri net model of the system takes into account normal behaviour, failures and reconfiguration mechanisms. Our approach uses linear logic as formal framework and is based on a backward and a forward reasoning. It derives feared scenarios as causal relationships between normal states and the feared one.     

Investigation of time selectivity of wireless channels through the use of RVC

A potential candidate that can be used for emulating different propagation environments is the reverberation chamber (RVC). Since mobility is of primary concern for wireless communication systems, understanding of its consequences is crucial. Mobility causes spectral broadening whose impact is generally evaluated through the observation of Doppler spectrum. In this study, investigation of Doppler spectrum characteristics through the use of an RVC and the methods for the purpose of its manipulation are presented. This study verifies that the Doppler spectrum can be manipulated in various ways. However, unless a precise setup is established it is almost impossible to obtain very specific Doppler shapes in RVCs such as widely known Jakes’ spectrum. Also, a different interpretation of mobility for wireless channels is given by the use of a new concept called motion intensity. This concept is elaborated in terms of both its technical aspects and its impact on wireless channel characterization.     

武汉光谷智能网联汽车配套基础设施总体架构及车路协同

智能网联汽车正进入快速发展阶段,汽车行业正进行颠覆性变革.武汉作为智慧城市基础设施与智能网联汽车协调发展第一批试点城市之一,正在积极探索智能网联汽车技术的发展和应用.结合武汉光谷智能网联汽车配套基础设施(花山示范段)工程实例,通过梳理网联汽车建设目标及建设内容,着重探讨平台系统应用场景建设、车路协同应用场景建设及总体架...     

Data City: Urban Metabolic Decision Processes

Designer and computational specialist Daniel Segraves describes the decarbonisation tool that he has helped develop in collaboration with Chicago-based Adrian Smith + Gordon Gill Architects and the Argonne National Laboratory Computation Department. The creation of the multi-scale analytic model focusing on the embodied and expended carbon of urban systems allows for energy performance to be tracked across a wider region, encompassing multiple buildings and agents.     

A predictive model of the effects of genotypic,pre‐ and postharvest stages on barley β‐glucan levels

BACKGROUND: β‐Glucan is a bioactive component of cereal grains that has many potential uses and health‐promoting benefits. Recent research has focused on improving the nutritional value of food by increasing human exposure to β‐glucan. This study looks at the development of a farm‐level baseline model (including scenario analysis) to evaluate the impact of pre‐ and postharvest stages (including genotypic factors, environmental conditions, agronomic factors and storage) on β‐glucan levels in barley. Monte Carlo simulation techniques were employed to model various stages in pre‐ and postharvest processes and to simulate the factors influencing the level of β‐glucan content in both hulled barley (H_B) and hull‐less barley (H_LB) genotypes. RESULTS: The baseline model found that the mean simulated level of β‐glucan was 40.99 and 56.77 g kg^?1 for H_B and H_LB genotypes respectively. A sensitivity analysis highlighted that genotype was the most important parameter in determining the final β‐glucan content (correlation coefficients of 0.66 and 0.78 for H_B and H_LB respectively), more so than any of the agronomic factors analysed. The scenario analysis highlighted the importance of harvest date (scenario 2) and storage conditions (scenario 3), with a potential 32.6 and 32.7% decrease in β‐glucan (compared with the baseline model) if harvesting is carried out early during physiological maturity (i.e. at growth stage 92) and a potential 20.1 and 19.5% increase in β‐glucan for H_B and H_LB respectively if storage time is minimised. CONCLUSION: This study predicted the influence of genotypic, pre‐ and postharvest operations on β‐glucan content and thus allows strategies to be identified to influence β‐glucan content in barley products. Copyright © 2008 Society of Chemical Industry     

A Methodology for Modeling and Optimizing Social Systems

Abstract

A system methodology for modeling and optimizing social systems is presented. It allows constructing dynamical models formulated stochastically, i.e., their results are given by confidence intervals. The models provide optimal intervention ways to reach the stated objectives. Two optimization methods are used: (1) to test strategies and scenarios and (2) to optimize with a genetic algorithm. The application case presented is a small nonformal education Spanish business. First, the model is validated in the 2008–2012 period, and subsequently, the optimal way to obtain a maximum profit in the 2013–2025 period is obtained using the two methods.     

Design and control of an AS/RS

Automated storage/retrieval systems (AS/RSs) are a combination of equipment and controls which automatically handle, store and retrieve materials (components, tools, raw material and subassemblies) with great speed and accuracy. Consequently, they are widely used in industrial companies to manage products with cost-effective utilization of time, space and equipment. This paper presents a multi-parametric dynamic model of a product-to-picker storage system with class based storage allocation of products. Thousands of what-if scenarios are simulated in order to measure the impact of alternative design and operating configurations on the expected system performance and to identify the most critical factors and combinations of factors affecting the response of the system. Class based storage proves to be a very effective way of both reducing the picking cycle time and maximizing the throughput of the system. The rapid effectiveness of visual interactive simulation (VIS) in supporting the design (redesign) and control of new (existing) warehouses emerges, responding to the need for flexibility which modern companies need in order to adapt to strongly changing operating conditions quickly.     

太赫兹通信关键技术与发展愿景

6G研究已启动,太赫兹通信技术以其支持超大带宽资源和超高通信速率等技术特点成为未来6G愿景实现的关键候选技术。从太赫兹通信技术特点出发,讨论了太赫兹通信未来可能的应用场景,系统分析了太赫兹通信的关键技术方向、产业发展现状与面临挑战,最后提出了未来太赫兹通信技术的目标愿景与发展建议。     

6G太赫兹传输链路特性分析

6G时代,太赫兹技术将实现Tbit/s的超高容量,而更高频点电磁波将面临更为复杂的链路传播环境。分别介绍了太赫兹在晴朗空气、雨天、雾天等场景的链路损耗,给出太赫兹可用频谱建议以及太赫兹适合室外短距离覆盖以及室内覆盖的结论,最后提出相应的6G太赫兹的应用场景建议。